Automatic Multi-Sensor Extrinsic Calibration For Mobile Robots

Autor: Ruben Gomez-Ojeda, Jose-Raul Ruiz-Sarmiento, Javier Gonzalez-Jimenez, David Zuñiga-Noël
Rok vydání: 2019
Předmět:
FOS: Computer and information sciences
Control and Optimization
Computer science
Calibration (statistics)
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Biomedical Engineering
02 engineering and technology
01 natural sciences
Set (abstract data type)
Computer Science - Robotics
Artificial Intelligence
Motion estimation
0202 electrical engineering
electronic engineering
information engineering
Computer vision
Ground plane
business.industry
Mechanical Engineering
010401 analytical chemistry
Mobile robot
0104 chemical sciences
Computer Science Applications
Human-Computer Interaction
Control and Systems Engineering
Metric (mathematics)
RGB color model
020201 artificial intelligence & image processing
Computer Vision and Pattern Recognition
Artificial intelligence
business
Robotics (cs.RO)
Zdroj: IEEE Robotics and Automation Letters
ISSN: 2377-3766
DOI: 10.1109/lra.2019.2922618
Popis: In order to fuse measurements from multiple sensors mounted on a mobile robot, it is needed to express them in a common reference system through their relative spatial transformations. In this paper, we present a method to estimate the full 6DoF extrinsic calibration parameters of multiple heterogeneous sensors (Lidars, Depth and RGB cameras) suitable for automatic execution on a mobile robot. Our method computes the 2D calibration parameters (x, y, yaw) through a motion-based approach, while for the remaining 3 parameters (z, pitch, roll) it requires the observation of the ground plane for a short period of time. What set this proposal apart from others is that: i) all calibration parameters are initialized in closed form, and ii) the scale ambiguity inherent to motion estimation from a monocular camera is explicitly handled, enabling the combination of these sensors and metric ones (Lidars, stereo rigs, etc.) within the same optimization framework. %Additionally, outlier observations arising from local sensor drift are automatically detected and removed from the calibration process. We provide a formal definition of the problem, as well as of the contributed method, for which a C++ implementation has been made publicly available. The suitability of the method has been assessed in simulation an with real data from indoor and outdoor scenarios. Finally, improvements over state-of-the-art motion-based calibration proposals are shown through experimental evaluation.
8 pages. 3 figures. IEEE Robotics and Automation Letters, 2019. Project webpage (code): http://github.com/dzunigan/robot_autocalibration
Databáze: OpenAIRE
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